This invention relates to systems for collecting and analyzing data and using analysis of data for performance monitoring and in particular to the use of such systems on tools that process substrates.
Substrate processing equipment is used to process a variety of different substrates in different industries. Semiconductor substrates, such as silicon wafers, generally go through multiple substrate processing tools during manufacture of integrated circuits. Such tools perform different processes including cleaning, depositing material, removing material, forming patterns on the substrate and heating the substrate. Some tools have different modules that perform different processes such as a cleaning process in a cleaning module prior to a deposition process in a deposition module. Some tools have the capability to perform multiple tasks in the same process chamber such as both a cleaning step and a process step. Tools are also used to perform measurements on substrates at various points in the production of integrated circuits. Within a tool or a module, a process takes place that may affect the substrate in some way. Careful control of a process may be necessary in order for the integrated circuit produced to perform properly. For example, when a layer is deposited, it must generally have a thickness that is within a particular range. This range must be maintained across the substrate so that each integrated circuit has a layer of the correct thickness. Otherwise, some integrated circuits on a substrate may have too thick or too thin a layer and may not function correctly. To maintain control of a process, there may be certain process parameters that need to be controlled. For example, temperature, pressure, gas flow rate or chemical concentration may need to be carefully controlled. In addition to controlling a process parameter for a process module in general, the uniformity of a process parameter at different points across a substrate may also be controlled. Many tools include sensors to monitor such process parameters. Some tools use feedback and other types of control based on the measurements obtained from sensors. Substrate processing tools are used for other substrates including other semiconductor substrates such as Gallium Arsenide, Indium Phosphide and Indium Gallium Arsenide and for Flat Panel Display (FPD) substrates.
Various sensors are available for monitoring process parameters. Sensors may be used to measure properties such as temperature, pressure, gas flow rate, gaseous chemical composition within a chamber, position within a chamber, ion current density, ion current energy, light energy density, and vibration and acceleration of a wafer. Sensors may be mounted to a tool or may form part of a Process Condition Measuring Device (PCMD) such as those described in U.S. patent application Ser. No. 10/718,269 filed on Nov. 19, 2003, which application is hereby incorporated in its entirety by this reference. Sensors may be of different types depending on the process parameter they are to measure and the requirements of the environment in which they must work. Examples of sensors include thermocouples, pyrometers and thermistors for temperature, diaphragm sensors for pressure and vibration and optical sensors for position, endpoint and chemical composition measurement. Sensory information can also be obtained from the electrical values of process equipment actuators, control signals and internal or integrated sensors.
Tool health may be determined from measurements made by sensors. Tool health is a general term used to describe whether the tool is performing in an acceptable fashion. This generally means that it is achieving a designated process within some limits set by a user.
For certain applications it is useful to record data from a process tool in a separate unit called a data logger. The data may come from the tool through a communications port or may come from sensors or test points connected or dedicated to the data logger. The data are typically logged and later analyzed to better understand the process or to diagnose a problem that may exist in a process module. Current data loggers suffer from certain limitations. Dedicated leads or cables are generally needed for each sensor, sensors may be difficult to individually configure and software used to analyze data is often complex and difficult to customize for a particular application. Some currently used methods for reporting Sensor Data such as SECS/GEM typically report their data at a uniform or non-uniform frequency, sometimes a low frequency such as 1-5 Hertz or lower.
Therefore, there is a need for a user configurable data collection and analysis system. There is also a need for a data collection and analysis system that identifies process anomalies in a simple manner.